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https://www.researchgate.net/publication/221166079_Data_domain_description_using_support_vectors
Data domain description using support vectors. ... The proposed safe region model uses support vector data description to handle cases in high-speed trains where only normal data are available ...
https://www.semanticscholar.org/paper/Data-domain-description-using-support-vectors-Tax-Duin/572529f1350df7172ce2e96cd3b9f6461c12559b
This paper introduces a new method for data domain description , inspired by the Support Vector Machine by V.Vapnik, called the Support Vector Domain Description SVDD. This method computes a sphere shaped decision boundary with minimal volume around a set of objects. This data description can be used for novelty or outlier detection. It contains support vectors describing the sphere …
https://www.sciencedirect.com/science/article/pii/S0167865599000872
This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier detection.Cited by: 1711
https://www.sciencedirect.com/science/article/abs/pii/S0167865599000872
This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier detection. A spherically shaped decision boundary around a set of objects is constructed by a set of support vectors ...Cited by: 1711
http://rduin.nl/papers/prl_99_svdd.pdf
This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier de-
https://core.ac.uk/display/24697616
This data description can be used for novelty or outlier detection. It contains support vectors describing the sphere boundary and it has the possibility of obtaining higher order boundary descriptions without much extra computational cost. By using the di erent kernels this SVDD can obtain more exible and more accurate data descriptions.Author: David M. J. Tax and Robert P. W. Duin
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.91.7580
This paper introduces a new method for data domain description, inspired by the Support Vector Machine by V.Vapnik, called the Support Vector Domain Description (SVDD). This method computes a sphere shaped decision boundary with minimal volume around a set of objects. This data description can be used for novelty or outlier detection.
https://dl.acm.org/doi/10.1023/B%3AMACH.0000008084.60811.49
Data domain description concerns the characterization of a data set. A good description covers all target data but includes no superfluous space. The boundary of a dataset can be used to detect novel data or outliers. We will present the Support Vector Data Description (SVDD) which is inspired by the Support Vector Classifier.
https://dl.acm.org/citation.cfm?id=960109
Data domain description concerns the characterization of a data set. A good description covers all target data but includes no superfluous space. The boundary of a dataset can be used to detect novel data or outliers. We will present the Support Vector Data Description (SVDD) which is inspired by the Support Vector Classifier.Cited by: 2579
https://link.springer.com/article/10.1023%2FB%3AMACH.0000008084.60811.49
Jan 01, 2004 · Data domain description concerns the characterization of a data set. A good description covers all target data but includes no superfluous space. The boundary of a dataset can be used to detect novel data or outliers. We will present the Support Vector Data Description (SVDD) which is inspired by the Support Vector Classifier.Cited by: 2579
https://www.researchgate.net/publication/221166079_Data_domain_description_using_support_vectors
Data domain description using support vectors. ... The proposed safe region model uses support vector data description to handle cases in high-speed trains where only normal data are available ...
https://www.sciencedirect.com/science/article/pii/S0167865599000872
In Fig. 2, again a 2D artificial dataset containing 10 objects is shown.Now a support vector domain description with a Gaussian kernel for different values of s is used. The width parameter s ranges from very small (s=1.0 in the leftmost figure) to large (s=25.0 in the rightmost figure).Note that the number of support vectors decreases and that the description becomes more sphere-like.Cited by: 1711
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.91.7580
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Abstract. This paper introduces a new method for data domain description, inspired by the Support Vector Machine by V.Vapnik, called the Support Vector Domain Description (SVDD). This method computes a sphere shaped decision boundary with minimal volume around a set of objects.
https://www.semanticscholar.org/paper/Data-domain-description-using-support-vectors-Tax-Duin/572529f1350df7172ce2e96cd3b9f6461c12559b
This paper introduces a new method for data domain description , inspired by the Support Vector Machine by V.Vapnik, called the Support Vector Domain Description SVDD. This method computes a sphere shaped decision boundary with minimal volume around a set of objects. This data description can be used for novelty or outlier detection. It contains support vectors describing the sphere boundary ...
http://rduin.nl/papers/prl_99_svdd.pdf
This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier de-tection. A spherically shaped decision boundary around a set of objects is constructed by a set of support vectors
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.98.5622
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier detection. A spherically shaped decision boundary around a set of objects is constructed by a set ...
https://www.sciencedirect.com/science/article/abs/pii/S0167865599000872
This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier detection. A spherically shaped decision boundary around a set of objects is constructed by a set of support vectors ...Cited by: 1711
https://dl.acm.org/doi/10.1023/B%3AMACH.0000008084.60811.49
Data domain description concerns the characterization of a data set. A good description covers all target data but includes no superfluous space. The boundary of a dataset can be used to detect novel data or outliers. We will present the Support Vector Data Description (SVDD) which is inspired by the Support Vector Classifier.
https://link.springer.com/article/10.1023%2FB%3AMACH.0000008084.60811.49
Jan 01, 2004 · Data domain description concerns the characterization of a data set. A good description covers all target data but includes no superfluous space. The boundary of a dataset can be used to detect novel data or outliers. We will present the Support Vector Data Description (SVDD) which is inspired by the Support Vector Classifier.Cited by: 2579
https://link.springer.com/content/pdf/10.1023%2FB%3AMACH.0000008084.60811.49.pdf
We will present the Support Vector Data Description (SVDD) which is inspired by the Support Vector Classifier. It obtains a spherically shaped boundary around a dataset and analogous to the Support Vector Classifier it can be made flexible by using other kernel functions. The method is made robust against outliers in the training set and is ...Cited by: 2579
https://www.researchgate.net/publication/221166079_Data_domain_description_using_support_vectors
Data domain description using support vectors. ... The proposed safe region model uses support vector data description to handle cases in high-speed trains where only normal data are available ...
https://www.semanticscholar.org/paper/Data-domain-description-using-support-vectors-Tax-Duin/572529f1350df7172ce2e96cd3b9f6461c12559b
This paper introduces a new method for data domain description , inspired by the Support Vector Machine by V.Vapnik, called the Support Vector Domain Description SVDD. This method computes a sphere shaped decision boundary with minimal volume around a set of objects. This data description can be used for novelty or outlier detection.
https://www.sciencedirect.com/science/article/pii/S0167865599000872
This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier detection.Cited by: 1711
https://www.sciencedirect.com/science/article/abs/pii/S0167865599000872
This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier detection. A spherically shaped decision boundary around a set of objects is constructed by a set of support vectors describing the sphere boundary. It has the possibility of transforming the data …Cited by: 1711
https://www.semanticscholar.org/paper/Support-vector-domain-description-Tax-Duin/d9f0e1c7e240597992232840f7cb96ceeefa1940
This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier detection. A spherically shaped decision boundary around a set of objects is constructed by a set of support vectors describing the sphere boundary. It has the possibility of transforming the data …
https://core.ac.uk/display/24697616
This paper introduces a new method for data domain description, inspired by the Support Vector Machine by V.Vapnik, called the Support Vector Domain Description (SVDD). This method computes a sphere shaped decision boundary with minimal volume around a set of objects. This data description can be used for novelty or outlier detection.Author: David M. J. Tax and Robert P. W. Duin
http://rduin.nl/papers/prl_99_svdd.pdf
This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier de-tection. A spherically shaped decision boundary around a set of objects is constructed by a set of support vectors
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.91.7580
This paper introduces a new method for data domain description, inspired by the Support Vector Machine by V.Vapnik, called the Support Vector Domain Description (SVDD). This method computes a sphere shaped decision boundary with minimal volume around a set of objects. This data description can be used for novelty or outlier detection.
https://dl.acm.org/citation.cfm?id=960109
Data domain description concerns the characterization of a data set. A good description covers all target data but includes no superfluous space. The boundary of a dataset can be used to detect novel data or outliers. We will present the Support Vector Data Description (SVDD) which is inspired by the Support Vector Classifier.Cited by: 2579
https://link.springer.com/article/10.1023%2FB%3AMACH.0000008084.60811.49
Data domain description concerns the characterization of a data set. A good description covers all target data but includes no superfluous space. The boundary of a dataset can be used to detect novel data or outliers. We will present the Support Vector Data Description (SVDD) which is inspired by the Support Vector Classifier.Cited by: 2579
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